Author(s): Gneezy, Uri; Kajackaite, Agne; Sobel, Joel | Abstract: This paper studies lying. An agent randomly picks a number from a known distribution. She can then report any number and receive a monetary payoff based only on her report. The paper presents a model of lying costs that generates hypotheses regarding behavior. In an experiment, we find that the highest fraction of lies is from reporting the maximal outcome, but some participants do not make the maximal lie. More participants lie partially when the experimenter cannot observe their outcomes than when the experimenter can verify the observed outcome. Partial lying increases when the prior probability of the highest outcome decreases. (JEL C91, D12, D90, Z13)

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Lying Aversion and the Size of the Lie

Incentives and cheating

We modify the principal-agent model with moral hazard by assuming that the agent is expectation-based loss averse according to Koszegi and Rabin (2006, 2007). The optimal contract is a binary payment scheme even for a rich performance measure, where standard preferences predict a fully contingent contract. The logic is that, due to the stochastic reference point, increasing the number of different wages reduces the agent’s expected utility without providing strong additional incentives. Moreover, for diminutive occurrence probabilities for all signals the agent is rewarded with the fixed bonus if his performance exceeds a certain threshold.

Binary Payment Schemes: Moral Hazard and Loss Aversion

Over the past decade, a large and growing body of experimental research has analyzed dishonest behavior. Yet the findings as to when people engage in (dis)honest behavior are to some extent unclear and even contradictory. A systematic analysis of the factors associated with dishonest behavior thus seems desirable. This meta-analysis reviews four of the most widely used experimental paradigms: sender-receiver games, die-roll tasks, coin-flip tasks, and matrix tasks. We integrate data from 565 experiments (totaling N = 44,050 choices) to address many of the ongoing debates on who behaves dishonestly and under what circumstances. Our findings show that dishonest behavior depends on both situational factors, such as reward magnitude and externalities, and personal factors, such as the participant's gender and age. Further, laboratory studies are associated with more dishonesty than field studies, and the use of deception in experiments is associated with less dishonesty. To some extent, the different experimental paradigms come to different conclusions. For example, a comparable percentage of people lie in die-roll and matrix tasks, but in die-roll tasks liars lie to a considerably greater degree. We also find substantial evidence for publication bias in almost all measures of dishonest behavior. Future research on dishonesty would benefit from more representative participant pools and from clarifying why the different experimental paradigms yield different conclusions. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

The Truth About Lies: A Meta-Analysis on Dishonest Behavior

Errors in probabilistic reasoning have been the focus of much psychology research and are among the original topics of modern behavioral economics. This chapter reviews theory and evidence on this topic, with the goal of facilitating more systematic study of belief biases and their integration into economics. The chapter discusses biases in beliefs about random processes, biases in belief updating, the representativeness heuristic as a possible unifying theory, and interactions between biased belief updating and other features of the updating situation. Throughout, I aim to convey how much evidence there is for (and against) each putative bias, and I highlight when and how different biases may be related to each other. The chapter ends by drawing general lessons for when people update too much or too little, reflecting on modeling challenges, pointing to areas of economics to which the biases are relevant, and highlighting some possible directions for future work.

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Errors in Probabilistic Reasoning and Judgment Biases

Private information is at the heart of many economic activities. For decades, economists have assumed that individuals are willing to misreport private information if this maximizes their material payoff. We combine data from 90 experimental studies in economics, psychology, and sociology, and show that, in fact, people lie surprisingly little. We then formalize a wide range of potential explanations for the observed behavior, identify testable predictions that can distinguish between the models, and conduct new experiments to do so. Our empirical evidence suggests that a preference for being seen as honest and a preference for being honest are the main motivations for truth‐telling.

https://www.econstor.eu/bitstream/10419/194797/1/cesifo1_wp6087.pdf

Preferences for Truth‐Telling

Private information is at the heart of many economic activities. For decades, economists have assumed that individuals are willing to misreport private information if this maximizes their material payoff. We combine data from 72 experimental studies in economics, psychology and sociology, and show that, in fact, people lie surprisingly little. We then formalize a wide range of potential explanations for the observed behavior, identify testable predictions that can distinguish between the models and conduct new experiments to do so. None of the most popular explanations suggested in the literature can explain the data. We show that only combining a preference for being honest with a preference for being seen as honest can organize the empirical evidence.

https://papers.ssrn.com/sol3/Delivery.cfm/dp10188.pdf?abstractid=2840132&mirid=1

Preferences for Truth-Telling

Preferences for truth-telling

We examine the reference-dependent risk preferences of K} oszegi and Rabin (2007), focusing on their choice-acclimating personal equilibria concept. We relate their model to other existing generalizations of expected utility. We demonstrate that linear gain-loss choice-acclimating personal equilibria is equivalent to the intersection of quadratic utility and pessimistic rank-dependent utility. However, it has only a trivial intersection (i.e. expected utility) with other referencedependent preferences. We use these relationships to extend our understanding of K} oszegi and Rabin’s model: linking their functional form to behavior; demonstrating new applications; and deriving new tests and looking for support in existing experimental data. (98 words)

/pdf/a-behavioral-analysis-of-stochastic-reference-dependence-12724hpkja.pdf

A Behavioral Analysis of Stochastic Reference Dependence

People believe that, even in very large samples, proportions of binary signals might depart significantly from the population mean. We model this "non-belief in the Law of Large Numbers" by assuming that a person believes that proportions in any given sample might be determined by a rate different than the true rate. In prediction, a non-believer expects the distribution of signals will have fat tails. In inference, a non-believer remains uncertain and influenced by priors even after observing an arbitrarily large sample. We explore implications for beliefs and behavior in a variety of economic settings.

Collin Raymond

Papers

Preferences for Truth‐Telling

Preferences for Truth-Telling

Preferences for truth-telling

A Behavioral Analysis of Stochastic Reference Dependence

A model of nonbelief in the law of large numbers.